OpenAI eats jobs, then offers to help you find a new one at Walmart

Scope of AI-Driven Job Loss vs Hype

• Some argue “AI eating jobs” is overstated: many layoffs labeled as “AI-driven” are seen as normal cost-cutting in a downturn, with AI used as a convenient narrative for investors.
• Others provide concrete examples of impact: OCR and automation reducing data entry; MT reducing translator income; LLMs replacing tier-1 support, copywriting, basic coding, and junior developer roles; Salesforce and others citing AI for customer service cuts.
• Several commenters describe a more diffuse effect: productivity gains spread across teams leading to thinner hiring pipelines, unfilled backfills, and attrition instead of direct 1:1 replacement.

Productivity Gains, Quality, and “Entropy”

• Supporters say LLMs let fewer or less-experienced people handle more work (e.g., financial reconciliation, analytics, service desks), saving significant payroll versus small AI tooling costs.
• Skeptics counter that LLM “analysis” is often shallow and error-prone, comparable to a new intern, and that hidden long-term losses (lost expertise, brittleness, lack of redundancy) offset short-term savings.
• Historical analogies (law offices going digital, factory automation) are used to argue that tech typically lets one person replace a team; critics reply that slack and resilience are being stripped out.

Capital, Datacenters, and Who Benefits

• A recurring theme: money once paid as wages is redirected to datacenters, energy, and hardware vendors. Some see this as “AI taking jobs” without truly doing equivalent work.
• Others push back that datacenters also pay workers and can be considered “useful,” though concerns are raised about energy use, water consumption, and rapid hardware obsolescence.
• Several point out that automation gains mostly accrue to shareholders, not workers; automation is called unethical when it redistributes wealth upward without new opportunities for the displaced.

Ethics, Censorship, and Power

• Strong resentment that user-generated content (e.g., StackOverflow, open source, scraped web data) trains models that then help eliminate contributors’ jobs, without consent or compensation.
• “AI ethics/safety” is widely characterized as brand safety and PR theater, especially when combined with content restrictions while openly marketing job replacement.
• Debate over whether job automation is ethically neutral or beneficial overall collides with anxiety about concentrated corporate control and pervasive data surveillance.

OpenAI’s Jobs & Certification Push (Walmart)

• OpenAI’s plan to certify “AI fluency” for millions and match them with employers (highlighting Walmart retail roles) is seen by many as PR positioning for inevitable disruption, or a grasp for a new vertical.
• Some find the messaging “kafkaesque” or “like setting your house on fire then selling you a fire extinguisher”; others liken it to factory-closure retraining programs—self-interested but potentially useful.
• Confusion and debate over the Walmart angle: retail associate roles vs solid but geographically constrained engineering jobs; mention of Walmart tech layoffs and relocation requirements.